Warden — Control tower for every AI agent you run
One governance layer across every LLM and AI agent integration — Bedrock, Azure OpenAI, Gemini, and custom — with a live inventory, consistent guardrails, prompt injection detection, and a full audit trail.
- Orgs with an AI agent incident
- 88%
- Clouds, one control plane
- 3
- Prompt and output audit trail
- 100%
Warden is in active design with early-access partners. What you see here is the real assessment methodology and roadmap — we build the production platform around the first partners who commit.
Agentic AI outpaced its own governance
Every team shipping AI features is quietly expanding your attack surface.
Agent Sprawl, No Inventory
Teams stand up Bedrock, Azure OpenAI, and Gemini integrations independently. Most security teams cannot list every LLM call happening in production today.
Prompt Injection Is Unmonitored
A 2026 enterprise survey found 88% of organizations had a confirmed or suspected AI agent security incident in the prior year — most had no detection in place when it happened.
PII Leaks Through Prompts
Customer data flows into prompts and completions with no consistent redaction layer, especially in fast-shipped internal tools built outside a formal AI platform.
No Human Checkpoint on Agent Actions
Agents that can call tools, move money, or delete records often ship without a mandatory human-in-the-loop gate for high-risk actions.
Six layers of control, one dashboard
Discover Every Agent
Warden scans your cloud accounts, API gateways, and CI/CD pipelines to build a live inventory of every Bedrock, Azure OpenAI, Gemini, and custom LLM integration in production.
Apply Guardrails Consistently
Wraps every discovered integration with consistent content filtering, denied-topic controls, and PII redaction — built on the same Bedrock Guardrails and Azure AI Content Safety primitives our consulting team already implements for clients.
Detect Prompt Injection in Real Time
Monitors prompts and completions for injection patterns, jailbreak attempts, and anomalous tool-calling behavior, scored and alerted the moment they occur.
Log Every Prompt & Completion
A tamper-evident audit trail of every agent interaction — the evidence base you need for a compliance review or an incident postmortem.
Gate High-Risk Actions
Configurable human-in-the-loop checkpoints for actions above a risk threshold — financial transactions, data deletion, external communications.
One Governance Dashboard
A single control tower across every cloud and model provider — no more checking three separate consoles to know what your AI estate is doing.
Built for the people who get paged when AI goes wrong
CISOs & Security Teams
Need an actual inventory and control plane for agentic AI before the board asks what happens if one of these agents goes wrong.
Platform & AI Engineering Teams
Shipping multiple LLM-powered features across Bedrock, Azure OpenAI, and Gemini and need consistent guardrails without rebuilding them per project.
Compliance & Risk Officers
In regulated industries (healthcare, financial services) who need an audit trail for every AI-assisted decision, not just a policy document.
What's your AI agent risk score?
Four questions. The same scoring logic our team uses in real client assessments.
How many distinct LLM or AI agent integrations does your organization run in production?
We don't just sell governance — we build it today
We Already Build the Guardrails Layer
Our AI engineering team implements Bedrock Guardrails, Azure AI Content Safety, and Gemini safety filters as part of every foundation model engagement — Warden productizes that same expertise into a standing control plane.
Multi-Cloud From Day One
Unlike single-vendor security tools, we already work across AWS, Azure, and Google Cloud for our consulting clients — Warden is built cloud-agnostic from the start.
The Varcio Platform Proves We Ship Platforms
This isn't our first production SaaS product — the Varcio platform is live today doing exactly this kind of cross-cloud governance work, for cost instead of security.
Frequently asked questions
Warden is in early access — the risk assessment methodology on this page is real and something our team uses in client engagements today. The full monitoring platform is being built with our first design partners. If the assessment above shows real exposure, that's exactly the conversation worth having now.
Most AI security startups are single-cloud or single-model-provider focused. Warden is built by a team that already implements Bedrock, Azure OpenAI, and Gemini guardrails across real enterprise engagements — the governance layer is designed to work identically regardless of which model or cloud you're running.
You get direct input into what we build, priority implementation of the guardrails and monitoring your specific AI estate needs, and pricing that reflects being first — not a discount on a finished product, a seat at the table while it's built around real requirements.
No — the assessment on this page is a self-scored questionnaire based on how your organization currently manages AI agents. A deeper technical audit (the kind that produces an actual inventory) happens after an early-access conversation.
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